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Nonlinear model-predictive integrated missile control and its multiobjective tuning

机译：非线性预测模型的综合导弹控制及其多目标调整

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摘要

This Note first proposed a model-predictive integrated missile control. The model-predictive control system is aimed to improve control performance by commanding optimal accelerations. It was shown that, by being able to predict future kinematics and dynamics of the engagement, the control pushed the missile to be more responsive than when a conventional separated guidance-autopilot system was used. Furthermore, the integrated design circumvented the control lag present when the guidance-autopilot subsystems were implemented separately, improving the intercept accuracy under disturbance. Second, multiobjective tuning of the proposed control system was demonstrated by using a design approach that considered not only control performance but also implementation cost, based on required computational capacity, which is an important design consideration in model-predictive control. Tuning of a nonlinear Model-predictive control (MPC) was considered, thus extending the existing results in [16] for when a linear MPC was used. The result indicates that implementation of the proposed controller requires resources that are considerably more capable than that used for the simulation. This is not unexpected, knowing that MPC is computationally heavy. Retrospectively, the Note presents a design approach to assist a practitioner in designing the model-based missile controller with both performance and required computational capacity in mind, and it is not intended to proof practical feasibility of the proposed controller. The obtained results indicate what computational capacity is required to be able to implement the proposed controller, which is useful for the practitioner when designing the MPC for real-time implementation. The results also show an insight around the tradeoff between the two objectives upon which the practitioner can base his/her decisions on: for instance, the best performance for a given computational capacity and the sensitivity between the two competing objectives of performance and cost.
机译：本说明首先提出了一种可预测模型的集成导弹控制系统。模型预测控制系统旨在通过命令最佳加速度来改善控制性能。结果表明，与使用传统的分离制导-自动驾驶系统相比，这种控制方式能够预测导弹的未来运动学和动力学特性，从而使导弹具有更高的响应能力。此外，集成设计避免了单独实施制导自动驾驶仪子系统时的控制滞后，提高了干扰下的拦截精度。其次，通过使用一种设计方法证明了所提出的控制系统的多目标调整，该设计方法基于所需的计算能力，不仅考虑了控制性能，还考虑了实现成本，这是模型预测控制中的重要设计考虑因素。考虑了非线性模型预测控制（MPC）的调整，因此扩展了[16]中使用线性MPC时的现有结果。结果表明，所提出的控制器的实现需要比仿真所使用的资源强大得多的资源。知道MPC在计算上很繁琐，这并不意外。追溯地，本说明提出了一种设计方法，可帮助从业人员在设计基于模型的导弹控制器时兼顾性能和所需的计算能力，而无意于证明所提出控制器的实际可行性。获得的结果表明，要实现所提出的控制器需要多少计算能力，这对于从业人员在设计用于实时实现的MPC时很有用。结果还显示了围绕这两个目标之间权衡的见解，从业者可以根据其决策：例如，给定计算能力下的最佳性能以及性能和成本这两个相互竞争的目标之间的敏感性。

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  • 来源
    《Journal of guidance, control, and dynamics》 |2017年第11期|2958-2967|共10页
  • 作者

    Bachtiar Vincent; Manzie Chris; Kerrigan Eric C.;

  • 作者单位

    University of Melbourne, Department of Mechanical Engineering, Department of Electrical and Electronic Engineering, Melbourne, VIC, Australia;

    University of Melbourne, Department of Mechanical Engineering, Department of Electrical and Electronic Engineering, Melbourne, VIC, Australia;

    Imperial College London, Department of Electrical and Electronic Engineering, Department of Aeronautics, London, United Kingdom;

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